Estimating peanut leaf chlorophyll content with dorsiventral leaf adjusted indices: minimizing the impact of spectral differences between adaxial and abaxial leaf surfaces
Estimating peanut leaf chlorophyll content with dorsiventral leaf adjusted indices: minimizing the impact of spectral differences between adaxial and abaxial leaf surfaces
Relatively little research has assessed the impact of spectral differences among dorsiventral leaves caused by leaf structure on leaf chlorophyll content (LCC) retrieval. Based on reflectance measured from peanut adaxial and abaxial leaves and LCC measurements, this study proposed a dorsiventral leaf adjusted ratio index (DLARI) to adjust dorsiventral leaf structure and improve LCC retrieval accuracy. Moreover, the modified Datt (MDATT) index, which was insensitive to leaves structure, was optimized for peanut plants. All possible wavelength combinations for the DLARI and MDATT formulae were evaluated. When reflectance from both sides were considered, the optimal combination for the MDATT formula was (R723−R738)/(R723−R722) with a cross-validation R2cv of 0.91 and RMSEcv of 3.53 μg/cm2. The DLARI formula provided the best performing indices, which were (R735−R753)/(R715−R819) for estimating LCC from the adaxial surface (R2cv = 0.96, RMSEcv = 2.37 μg/cm2) and (R732−R754)/(R724−R773) for estimating LCC from reflectance of both sides (R2cv = 0.94, RMSEcv = 2.81 μg/cm2). A comparison with published vegetation indices demonstrated that the published indices yielded reliable estimates of LCC from the adaxial surface but performed worse than DLARIs when both leaf sides were considered. This paper concludes that the DLARI is the most promising approach to estimate peanut LCC.
Xie, Mengmeng
7162a09a-e6f9-40d2-a81a-affdc461631e
Zhang, Zhongqiang
73b30743-883a-485e-a7cc-53b272abe289
Huete, Alfredo
f53fc154-f0ae-4689-b187-b110f8668adb
Brown, Luke
3f3ee47e-ee1f-4a44-a223-36059b69ce92
Wang, Heyu
173c0ee4-ccda-4821-98db-1ca470c69ecf
Xie, Qiaoyun
4f002fc7-d22b-46b8-bcf9-9f1015d17eb9
Xu, Xingpeng
dad538b8-352a-418a-8bf6-db3dbb7ca2f6
Ding, Yanling
8c210587-5c29-4ace-960c-adc8557dc3ea
15 September 2019
Xie, Mengmeng
7162a09a-e6f9-40d2-a81a-affdc461631e
Zhang, Zhongqiang
73b30743-883a-485e-a7cc-53b272abe289
Huete, Alfredo
f53fc154-f0ae-4689-b187-b110f8668adb
Brown, Luke
3f3ee47e-ee1f-4a44-a223-36059b69ce92
Wang, Heyu
173c0ee4-ccda-4821-98db-1ca470c69ecf
Xie, Qiaoyun
4f002fc7-d22b-46b8-bcf9-9f1015d17eb9
Xu, Xingpeng
dad538b8-352a-418a-8bf6-db3dbb7ca2f6
Ding, Yanling
8c210587-5c29-4ace-960c-adc8557dc3ea
Xie, Mengmeng, Zhang, Zhongqiang, Huete, Alfredo, Brown, Luke, Wang, Heyu, Xie, Qiaoyun, Xu, Xingpeng and Ding, Yanling
(2019)
Estimating peanut leaf chlorophyll content with dorsiventral leaf adjusted indices: minimizing the impact of spectral differences between adaxial and abaxial leaf surfaces.
Remote Sensing, 11 (18).
(doi:10.3390/rs11182148).
Abstract
Relatively little research has assessed the impact of spectral differences among dorsiventral leaves caused by leaf structure on leaf chlorophyll content (LCC) retrieval. Based on reflectance measured from peanut adaxial and abaxial leaves and LCC measurements, this study proposed a dorsiventral leaf adjusted ratio index (DLARI) to adjust dorsiventral leaf structure and improve LCC retrieval accuracy. Moreover, the modified Datt (MDATT) index, which was insensitive to leaves structure, was optimized for peanut plants. All possible wavelength combinations for the DLARI and MDATT formulae were evaluated. When reflectance from both sides were considered, the optimal combination for the MDATT formula was (R723−R738)/(R723−R722) with a cross-validation R2cv of 0.91 and RMSEcv of 3.53 μg/cm2. The DLARI formula provided the best performing indices, which were (R735−R753)/(R715−R819) for estimating LCC from the adaxial surface (R2cv = 0.96, RMSEcv = 2.37 μg/cm2) and (R732−R754)/(R724−R773) for estimating LCC from reflectance of both sides (R2cv = 0.94, RMSEcv = 2.81 μg/cm2). A comparison with published vegetation indices demonstrated that the published indices yielded reliable estimates of LCC from the adaxial surface but performed worse than DLARIs when both leaf sides were considered. This paper concludes that the DLARI is the most promising approach to estimate peanut LCC.
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remotesensing-11-02148
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Accepted/In Press date: 11 September 2019
Published date: 15 September 2019
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Local EPrints ID: 434221
URI: http://eprints.soton.ac.uk/id/eprint/434221
ISSN: 2072-4292
PURE UUID: 668bb86f-c841-4c65-9cfe-bc7bbd66a4e0
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Date deposited: 17 Sep 2019 16:30
Last modified: 04 Oct 2024 18:06
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Author:
Mengmeng Xie
Author:
Zhongqiang Zhang
Author:
Alfredo Huete
Author:
Luke Brown
Author:
Heyu Wang
Author:
Qiaoyun Xie
Author:
Xingpeng Xu
Author:
Yanling Ding
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